BecomeMore : Affirmations

BecomeMore : Affirmations

TrustMRR

BecomeMore is a motivational and wellness iOS app designed to help you start and end your day with greater calm, confidence, and clarity. Discover positive affirmations, soothing visual themes, and a

BecomeMore is a motivational and wellness iOS app designed to help you start and end your day with greater calm, confidence, and clarity. Discover positive affirmations, soothing visual themes, and a simple experience to support you in your daily life.

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Actual performance

13customers
$50MRR/mo
Did not reach leaderboard

Traction signals

MRR growth 30d+239.3%

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual · Missing: mac, agents, macos
22%22% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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